Performance of particle swarm optimization techniques on papr reduction for OFDM systems

Partial transmit sequence (PTS) technique requires an exhaustive search over all combinations of allowed phase weighting factors, the search complexity increases exponentially with the number of sub-blocks. In this paper, a novel combing strategy that employs sub-block partition scheme and phase factors for PTS in orthogonal frequency division multiplexing (OFDM) system is proposed. We present an OFDM system, which through the use of sub-optimal PTS based on particle swarm optimization (PSO) algorithm, achieves low computation complexity to find optimum phase weighting factors and reduce the peak-to-average power ratio (PAPR). Furthermore, to work around potentially computational intractability, the proposed scheme exploits heuristics in consideration of both global and local exploration partial transmit sequence. Simulation results show that the proposed PSO-based PTS can efficiently find the optimum phase weighting factor, and can achieve the lower PAPR with moderate complexity.